NDLI: Accelerometry-based prediction of movement dynamics for balance monitoring

Content Provider	Springer Nature Link
Author	Fuschillo, Valeria Lucia Bagalà, Fabio Chiari, Lorenzo Cappello, Angelo
Copyright Year	2012
Abstract	This paper proposes a 2D functional evaluation tool for estimating subject-specific body segment parameters, which uses a simple motor task (repeated sit-to-stand, rSTS), recorded with one single-axis accelerometer (SAA) per segment and a force plate (FP). After this preliminary estimation, the accelerometer alone is used to make quasi-real-time predictions of ground reaction force (anterior/posterior, F $_{ X }$, and vertical, F $_{ Z }$, components), center of pressure (CoP) and center of mass (CoM), during rSTS and postural oscillation in the sagittal plane. These predicted dynamic variables, as well as those obtained using anthropometric parameters derived from De Leva, were compared to actual FP outputs in terms of root mean-squared errors (RMSEs). Using De Leva’s parameters in place of those estimated, RMSEs increase from 12 to 21 N (F $_{ X }$), from 21 to 24 N (F $_{ Z }$), and from 21.1 to 55.6 mm (CoP) in rSTS; similarly, RMSEs increase from 3.1 to 3.3 N (F $_{ X }$) and from 5.5 to 6.6 mm (CoP) in oscillatory trials. A telescopic inverted pendulum model was adopted to analyze the balance control in rSTS using only predicted CoP and CoM. Results suggest that one SAA per segment is sufficient to predict the dynamics of a biomechanical model of any degrees of freedom.
Starting Page	925
Ending Page	936
Page Count	12
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	50
Issue Number	9
e-ISSN	17410444
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-07-18
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Balance Subject-specific anthropometric parameters Movement dynamics prediction Accelerometers Force plate Human Physiology Biomedical Engineering Imaging Radiology Computer Applications
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

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